Side-by-side comparison of AI visibility scores, market position, and capabilities
Emitwise provides enterprise greenhouse gas management software with automated Scope 3 supply chain emissions calculation powered by machine learning.
Emitwise is a climate technology company founded in 2019 in London that has raised $15M to build enterprise GHG management software with a particular focus on automating the most difficult part of carbon accounting: Scope 3 supply chain emissions. The platform uses machine learning to classify procurement spend data into emissions categories, apply appropriate emissions factors, and calculate upstream and downstream emissions at scale without requiring suppliers to provide primary emissions data. This automated spend-based approach enables companies to quickly establish Scope 3 baselines that would otherwise require months of manual data collection. Emitwise integrates with ERP systems including SAP and Oracle to pull spend data automatically and provides supplier engagement tools for collecting primary emissions data from key suppliers over time. The company serves medium and large enterprises in manufacturing, retail, and professional services that have committed to science-based targets and need to address their supply chain emissions. Emitwise has found strong market fit in Europe where regulatory pressure from CSRD and customer expectations are driving corporate investment in Scope 3 measurement capabilities.
Serverless GPU cloud platform for AI/ML with Python-native deployment and per-second billing; developer-favorite scaling from zero competing with Replicate and Beam for AI compute.
Modal is a serverless cloud computing platform purpose-built for AI and machine learning workloads — providing on-demand GPU compute that scales instantly from zero with per-second billing, container management, distributed training support, and a Python-native developer experience that makes running ML workloads in the cloud feel as simple as running code locally. Founded in 2021 in New York City and backed by Redpoint Ventures and other investors, Modal has grown rapidly as AI development has accelerated demand for flexible, developer-friendly GPU infrastructure.\n\nModal's developer experience is its primary differentiator — engineers write Python functions decorated with @modal.function() and deploy them to the cloud with a single command, with Modal handling container building, GPU provisioning, auto-scaling, and execution. The platform supports training jobs that need distributed compute across multiple GPUs, model serving endpoints that scale to zero when unused (eliminating idle GPU costs), and batch inference jobs that process large datasets. The per-second billing model means developers pay only for actual compute time, not provisioned instances.\n\nIn 2025, Modal competes in the AI infrastructure market with Replicate, Beam, Banana, and major cloud providers' managed ML services (AWS SageMaker, Google Vertex AI, Azure ML) for serverless GPU compute. The market for AI-specific cloud infrastructure has grown dramatically as the number of ML engineers deploying models to production has expanded — traditional cloud providers require significant DevOps expertise to use GPU instances effectively, while Modal's Python-native approach reduces the barrier to entry. Modal has attracted a strong developer following among AI researchers and ML engineers building production AI applications. The 2025 strategy focuses on growing the developer community, adding enterprise features (dedicated GPU capacity, private networking, compliance), and expanding the hardware options available (H100 GPUs, custom accelerators).
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